From Machinery to Insights: A Comprehensive Data Acquisition Approach for Battery Cell Production

To ensure the widespread use of sustainably produced battery cells, further progress in research is needed. The transition to automated data acquisition is complicated by the technical complexity of industrial data acquisition. Existing software solutions also fall short in meeting usability, reproducibility, extensibility, and cost-effectiveness requirements for research-scale battery production lines. To address these gaps, this paper presents and evaluates a comprehensive data acquisition and collection solution for research-scale battery production lines. It offers a systematic overview of the industrial data acquisition process, focusing on gathering data from various existing machinery and utilizing the industry standard OPC UA protocol. Given the lack of existing solutions that meet the specified requirements, the paper introduces the "ProductionPilot" software as a solution. "ProductionPilot" is designed to provide an extensible platform with a user-friendly web interface. It enables users to select, structure, monitor, and export live production data delivered via OPC UA. The effectiveness of the proposed system is validated at the CELLFAB battery production research facility at eLab of RWTH Aachen university, demonstrating its capability for long-term data acquisition and the generation of digital shadows. By addressing the limitations of current data collection methods and providing a comprehensive solution, this research aims to facilitate the broader adoption of lithium-ion batteries in renewable energy applications

Potentials and Implementation Strategies For Flexible Battery Cell Production

The effects of a fossil fuel-based economy are becoming increasingly apparent. The storage and use of renewable energy sources are a key strategy to reduce overall greenhouse gas emissions. In this context, the demand for batteries as a suitable medium for energy storage is increasing rapidly. Lithium-ion batteries pioneered in consumer electronics are nowadays used in ever more applications, with the e-mobility sector being one of the most prominent. From a production perspective, the process chain for manufacturing of such lithium-ion batteries can be divided into three main sections: electrode production, cell assembly and cell finishing. However, actual implementation of the process chain differs substantially, depending on the selected cell format (pouch, cylindric, prismatic) and design, manifesting in cell-specific processes (e.g. stacking vs. winding), supplementary and/or omitted process steps and manufacturing technologies (e.g. pouch foil heat sealing vs. hard case laser welding). Currently there is no strictly preferred cell format, as each format has its advantages and disadvantages, depending on its intended application and system integration. Production of different battery cell types thus is spread across various international mostly Asian manufacturers, most of which have large scale mass production lines dedicated to a single specific format. Only a few manufacturers have a portfolio of formats (e.g. round and prismatic) in large quantities. Against this background, the following paper provides an overview of the product variety of lithium-ion batteries available on the market, following up with a discussion of potentials and implementation strategies for flexible battery cell production. First, applications and business areas for lithium-ion batteries are analysed and general flexibility areas regarding the battery cell design are derived. Subsequently, the impacts of the different flexibility areas on the production processes are analysed. In a final step, different implementation strategies and approaches for increased flexibility in battery cell production are elaborated

Deficits Of Innovation Management In The Application To The Disruptive Battery Industry

With the electrification of the automotive industry and the resulting demand for batteries, Gigafactories are increasingly established by battery cell manufacturers or new players, especially in Europe, and North America. When planning Gigafactories, there are various planning challenges due to the high and long-term investments. In particular, the variety of innovations and short innovation cycles creates uncertainty in the planning process. Reviewing the background provided, the application of existing approaches from innovation management to the current battery industry was assessed in this paper. For this, the environment of battery production was first examined in more detail, resulting in the identification of the relevant requirements for an innovation management method. Based on this, standard methods of innovation management were examined and evaluated based on the derived requirements. The evaluation showed that standard methods of innovation management only partially fulfil some of the requirements, highlighting the necessity of a dedicated method for the battery industry. In conclusion, the deficits and potential levers for successful innovation management are discussed

Digital Twin in the Battery Production Context for the Realization of Industry 4.0 Applications

Due to the worsening climate change drastic changes in the transportation sector are necessary. Crucial factors for sustainable energy supply are reliable and economical energy storage systems. Associated with that is the development of gigafactories with a capacity of up to 1000 GWh in 2030 in Europe (currently 25 GWh) for the production of battery cells especially for the automotive sector, which is one of the largest emitters of greenhouse gases in Europe. In addition to the required investments, high scrap rates due to unknown interdependencies within the process chain represent a central challenge within battery cell production. Another key challenge in series production is the product tracking along the value chain, which consists of continuous, batch and discrete processes. Because of it complexity the battery cell production industry is predestined for Industry 4.0 applications in order to meet the current challenges and to make battery cell production more efficient and sustainable. Digital twins and the use of AI algorithms enable the identification of previously unknown cause-effect relationships and thus a product improvement and increased efficiency. In this paper, the digital twin of a battery cell production will be developed. For this purpose, general requirements for the field of battery cell production are first determined and relevant parameters from the literature as well as from a production pilot line are defined. Based on the requirements and the selected parameters a corresponding structure for the digital twin in battery cell production is built and explained in this contribution. This provides the basis for measures to optimize production, such as predictive quality

Hype Cycle Assessment Of Emerging Technologies For Battery Production

The demand for battery-powered electric vehicles is growing rapidly as more and more OEMs are shifting their strategy towards an all-electric vehicle fleet. The lithium-ion battery cell is considered as the core component in terms of performance, range and price of electric vehicles. Since the development of the functional principle of the lithium-ion battery, both the product and the associated production technology have evolved significantly. OEMs, start-ups, equipment suppliers and other players in the automotive industry are investing heavily in research and development of various technologies to improve both the battery as a product and its production. An essential aspect is to enable sustainable battery production. While breakthroughs in battery technology are regularly announced, the actual merits of the technologies and the potential remain uncertain until commercial deployment. The aim of this paper is to systematically identify upcoming breakthroughs and announced innovations to provide an overview of promising battery technologies that companies should focus on to enable the planning of resilient and sustainable production systems. Hence, a hype cycle assessment following Gartner was adopted as the underlying approach to evaluate battery technologies for deployment in electromobility and mass production. First, various technologies, innovations, research activities and announcements in the field of battery technologies were screened, recorded and classified in order to obtain an overview of the current state of developments on both product and production levels. This includes an overview of innovations in battery design and configuration as well as process technologies and production systems. Subsequently, these technologies are evaluated according to predefined evaluation criteria in order to enable a systematic classification of the individual technologies in the hype cycle. The result is a consolidated overview of emerging battery technologies for sustainable battery production and a display for further recommendations for relevant companies and stakeholders

Synthesis of Artificial Coating Images and Parameter Data Sets in Electrode Manufacturing

Driven by continuous cost pressure and increasing market requirements, the optimisation of the lithium-ion battery production is focus of attention. In order to save time and costs, machine learning (ML) represent a promising tool. ML methods are able to analyse highly complex correlations and abstract data sets. But a considerable amount of training data is needed. Since data is not always available to the required extent, approaches for synthesising artificial data were investigated. In this study, the quality and corresponding measurement parameters in electrode production were assessed and selected. Based on this selection, coating trials have been conducted and the corresponding data set collected. The data set forms the basis for synthesis of artificial coating images and parameters. The selection and design of the synthesis models was divided into two sub-steps. First, the synthesis of artificial coating images was investigated. This was followed by the consideration of a procedure for the synthesis of structured data sets. A promising method for data synthesis of (coating) images are Generative Adversarial Networks (GAN). The basic idea of GANs is to oppose two models: a discriminator and a generator. The generator generates artificial data samples that match the input of the training dataset. Afterwards those data samples (both input and artificial data) are introduced to the discriminator. The discriminator's function is to identify whether the data presented originates from the training dataset or whether it is a counterfeit (artificial data) of the generator. The requirements for the synthesis of tabular data sets correspond in principle to those for a multivariate regression analysis. The combination of the models resulted in a method that allows the prediction of the corresponding measured quality values for arbitrarily selected process parameters, as well as the visualisation of the associated coating result in the form of an artificial image

Laser Drying Of Graphite Anodes For The Production Of Lithium-Ion Batteries - A Process- And Material-Side Analysis For Sustainable Battery Production

In many industries, such as the automotive industry or consumer electronics, the demand for lithium-ion batteries is increasing significantly. The state of the art in battery production is energy-consuming and cost-intensive. The drying process of the viscous active material applied to the conductor foils, together with the coating process, is responsible for more than half of the production costs of an electrode. The high energy consumption of conventional drying processes, such as convection drying, must be reduced. Therefore, lasers are used to dry the active material of the electrodes. Further advantages are the low footprint and the increased process flexibility. Moreover, the controlled energy deposition and the spatially selective heat input increase the energy efficiency of the process innovation laser drying. In this review, the results of experiments on drying anodes by laser are compared with the results of convection drying. For this purpose, different production process parameter combinations and material compositions for anodes are chosen in order to be able to derive the process and material influences on the electrode quality

A Review of Process Innovations in the Cell Finishing of Lithium-Ion Batteries in Large-Scale Production

The European Union's ambitious climate targets will make climate-friendly storage technologies essential. More than any other, this decade could be marked by battery technology, especially the lithium-ion battery (LIB). In addition, various trends in mobility and consumer electronics are spurring the cross-industry use of this secondary storage device. As a result, the need for additional production capacities is rising, and the need for vertical integration of the value chain of LIB in Europe. In current forecasts, Europe has a considerable deficit between battery cell demand and production capacities. The deficit highlights the need for additional capacities and effort to develop new production systems. Furthermore, production technologies remain challenging, as high reject rates are expected initially, and a reduction of costs at the battery cell level is mandatory. Formation and aging as part of the cell finishing are the production steps with the highest processing time and space requirements. The formation can take up to 24 hours, and the subsequent aging between 8 to 36 days. It thus represents the biggest bottleneck. In large-scale production, various process innovations are being worked on, depending on the degree of automation. However, a systematic study of the impact of these process innovations is hardly ever carried out. Various approaches are conceivable here: Innovative formation protocols, optimized plant technology, flexible goods carrier systems and other process-related innovations. This paper provides researchers and industry experts with meaningful insights into the status quo and future developments in the cell finishing of battery cells through a comprehensive research approach. These trends will be presented and systematically evaluated to identify the most significant levers to reduce costs and time. It reviews process innovations in cell finishing to approach this research gap and aims to answer how these innovations will benefit and shape the large-scale production of lithium-ion battery cells

Exploring mechanisms of sex differences in longevity: lifetime ovary exposure and exceptional longevity in dogs

To move closer to understanding the mechanistic underpinnings of sex differences in human longevity, we studied pet dogs to determine whether lifetime duration of ovary exposure was associated with exceptional longevity. This hypothesis was tested by collecting and analyzing lifetime medical histories, age at death, and cause of death for a cohort of canine ‘centenarians’– exceptionally long-lived Rottweiler dogs that lived more than 30% longer than average life expectancy for the breed. Sex and lifetime ovary exposure in the oldest-old Rottweilers (age at death, ≥ 13 years) were compared to a cohort of Rottweilers that had usual longevity (age at death, 8.0–10.8 years). Like women, female dogs were more likely than males to achieve exceptional longevity (OR, 95% CI = 2.0, 1.2–3.3; P= 0.006). However, removal of ovaries during the first 4 years of life erased the female survival advantage. In females, a strong positive association between ovaries and longevity persisted in multivariate analysis that considered other factors, such as height, body weight, and mother with exceptional longevity. A beneficial effect of ovaries on longevity in females could not be attributed to resistance against a particular disease or major cause of death. Our results document in dogs a female sex advantage for achieving exceptional longevity and show that lifetime ovary exposure, a factor not previously evaluated in women, is associated with exceptional longevity. This work introduces a conceptual framework for designing additional studies in pet dogs to define the ovary-sensitive biological processes that promote healthy human longevity

Spiral Defect Chaos in Large Aspect Ratio Rayleigh-Benard Convection

We report experiments on convection patterns in a cylindrical cell with a large aspect ratio. The fluid had a Prandtl number of approximately 1. We observed a chaotic pattern consisting of many rotating spirals and other defects in the parameter range where theory predicts that steady straight rolls should be stable. The correlation length of the pattern decreased rapidly with increasing control parameter so that the size of a correlated area became much smaller than the area of the cell. This suggests that the chaotic behavior is intrinsic to large aspect ratio geometries.Comment: Preprint of experimental paper submitted to Phys. Rev. Lett. May 12 1993. Text is preceeded by many TeX macros. Figures 1 and 2 are rather lon